Queuing access to a shared power supply

ABSTRACT

A method of queuing access to a power supply shared by a set of electrical access points. The access points turn on independently from one another and thus have independent power draws. Each access point has a specific power draw when on. The on state and associated power draw of each of access point is identified, and a load duration curve for each access point is normalized (i.e., combined with load duration curve(s)) from the other access points) into a probability distribution function. The probability distribution function is a normalized load duration curve that thus accounts for a varying set of “operating states” that may occur with respect to the set of access points (when viewed collectively). Each operating state has an associated probability of occurrence. As the operating state of the set (of access points) changes, access to the power supply is selectively queued, or de-queued (if previously queued).

COPYRIGHT STATEMENT

This application includes subject matter that is protected by copyright.All rights are reserved.

BACKGROUND OF THE INVENTION

Technical Field

The subject matter of this disclosure relates generally to regulatingelectric power.

Background of the Related Art

The modern electric utility industry began in the 1880s. It evolved fromgas and electric carbon-arc commercial and street lighting systems. Thefirst electricity generating station introduced the industry byfeaturing the four key elements of a modern electric utility system:reliable central generation, efficient distribution, a successfulend-use (the light bulb), and a competitive price. When the main andonly end-use of electric power was nighttime light bulbs, reliablecentral generation meant that electric power supply service wasavailable all of the time for all of the electric power demand. In thelate 1880s, power demand for electric motors brought the industry frommainly nighttime lighting to 24-hour service and dramatically raisedelectricity demand for transportation and industry needs. In addition,the original direct current (DC) electric system was quickly replaced bylow frequency (50-60Hz) alternating current (AC) systems.

Due to the critical importance of electric power in the economicdevelopment of society, the core electric system engineering planningrequirement for a reliable electric power supply was broadly definedunder the assumption of power supply availability all of the time forall electric demand end-uses. Electric power systems have historicallybeen dimensioned to handle its annual coincident peak demand. Tariffsare based on the situation when there is peak demand. All theseassumptions led to the engineering of an electric power infrastructurewhere supply growth (generation capacity power in Watts) constantlyoutpaces demand growth (average demand power in Watts). Electric powergeneration capacity has grown faster than average demand capacity sincethe industry inception, while the ratio of average demand power bygeneration capacity power (capacity factor) has steadily been between40-50%. Today, appliances have unrestricted access to electric power.Many sensor-automated appliances respond to environmental factorswithout human interaction. For instance, weather variation causes powerdraw synchronization on temperature-sensing appliances such asrefrigerators and air conditioners. When multiple appliances draw powersynchronously, a resonant coincident peak demand phenomenon occurs.

Electric utilities are accountable for delivering power to theirend-user customers 100% of the time. Those same customers pay forimmediate access to power to serve their needs, applying that power todrive a broad range of electric appliances that meet specific end userrequirements. Peak demand occurs when the need for power, i.e. customerutilization of power to operate their electric appliances, exceeds thebase load generating capacity of a local ISO/RSO network. Thiscoincident peak event triggers the acquisition of additional/higher costgenerating capacity by the utility provider to meet their reliabilityobligation, the costs of which often are passed directly on to theircustomers.

Electric utility customers may have either a single building/propertywith many operating appliances and/or a number of buildings/propertiesspread across one or more metropolitan geographies (an operatingenvironment). Within either a given building/property or MetropolitanService Area (MSA), a set of common internal and external environmentalfactors will be evident, as in a range of + or −2 degrees Fahrenheitoutside air temperature within the MSA or a similar narrow range oftemperatures room-to-room within a customer's building/property. In anygiven operating environment, electric appliances with a similarfunction, e.g., sensor-automated environmental cooling, will exhibit ahigh degree of synchronous “on/off” operational behaviors. Thus, forexample, it has been found that these appliances (such as airconditioners and refrigerators) demanded power simultaneously a highpercentage of the time to maintain end-user operational objectives suchas a target room temperature. When the majority of appliances are “on”simultaneously, a coincident peak is generated, requiring additionalelectric power supply resources to meet the appliances' electric powerdemand. A coincident peak demand event, which typically occurs less than5% of the time during a given billing cycle, nevertheless can accountfor over 20% of the total cost of power charged by an electric utilityto its end user customers.

There is a need in the art to provide a system that regulates anelectric appliance's access to its power supply to systematicallycontrol coincident peak demand. This disclosure addresses this need.

BRIEF SUMMARY

A method of queuing access to a power supply shared by a set ofelectrical access points is described. The access points can turn on andoff independently from one another and thus have independent powerdraws. The access points typically are also located remote from oneanother. One or more electrical appliances or devices may be associatedto a particular access point. Each access point has a specific powerdraw when it is on (i.e. drawing power from the power supply). Accordingto this disclosure, the on state and associated power draw of each ofaccess point is identified, and a load duration curve for each accesspoint is normalized (i.e., combined with load duration curve(s)) fromthe other access points) into a probability distribution function. Theprobability distribution function is a normalized load duration curvethat thus accounts for a varying set of “operating states” that mayoccur with respect to the set of access points (when viewedcollectively). Thus, if there are “n” access points, there are 2^(n)possible operating states for the access point set, with each operatingstate being represented by a set of simultaneous “events” correspondingto some subset of the access points (which subset may include all of theaccess points) being “on” or “off,” as the case may be. Each operatingstate has an associated probability of occurrence. According to themethod, as the operating state of the set (of access points) changes (asrepresented by the on/off events), access to the power supply isselectively queued, or de-queued (if previously queued).

The probability of occurrence of a particular operating state may beassociated with a grade of service (GoS), where GoS is a probability ofelectric power access being queued for more than a specified timeinterval. In a preferred embodiment, the probability distributionfunction is a transformed (or “non-normalized”) Erlang C probabilitydistribution that models a load duration curve (representing thecombined set of access points) that associates total power demand for agiven GoS.

In a representative, but non-limiting embodiment, the above-describedmethod is implemented in a centralized computing device (sometimesreferred to as a “power router”), and each access point is implementedin a switch, such as a digital electronic switch. According to thedescribed approach, and assuming queuing is not then in effect (an“available” mode), when an operating state probability (representing aparticular GoS) is met or exceeded, the system enters a queuing (or“busy”) mode to thereby control the “time” at which one or more accesspoints may then access the shared power supply. Preferably, theparticular turn-on “time” for an access point is controlled using an“access priority code” that the power router provides to the digitalelectronic switch located at an access point. The power routercontinually generates the access priority codes and provides these codesto the switches according to the queuing scheme. At a particularpoint-in-time, a set of access priority codes (APCs) thus defines arelative queuing order of the access points that minimizes individualaccess point queuing time and power draw collisions from the powersupply.

The foregoing has outlined some of the more pertinent features of thesubject matter. These features should be construed to be merelyillustrative. Many other beneficial results can be attained by applyingthe disclosed subject matter in a different manner or by modifying thesubject matter as will be described.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention and theadvantages thereof, reference is now made to the following descriptionstaken in conjunction with the accompanying drawings, in which:

FIG. 1 is a power supply capacity plot;

FIG. 2 illustrates a load duration curve (LDC) for an electric system;

FIG. 3 illustrates an electric system LDC modeled by a transformedErlang B distribution;

FIG. 4 illustrates an electric system LDC modeled by a transformedErlang C distribution;

FIG. 5 illustrates a comparison of the electric system LDC models inFIG. 3 and FIG. 4;

FIG. 6 illustrates how an EAPR executing the queuing access method ofthis disclosure controls coincident peak demand with respect to a powersupply shared among a set of access points;

FIG. 7 illustrates a system that incorporates the queuing access controlmethod of this disclosure;

FIG. 8 illustrates another embodiment of the system shown in FIG. 7;

FIG. 9 illustrates an interaction between a digital electronic switch(DES) of this disclosure and the EAPR;

FIG. 10 is a flowchart illustrating the queuing prioritization techniqueof this disclosure:

FIG. 11 illustrates a representative digital electronic switch (DES)configuration; and

FIG. 12 is a plot that represents a statistical measure of an appliancedraw at an access point.

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

As described above, this disclosure concerns a method of queuing accessto a power supply shared by a set of electrical access points. Theaccess points can turn on and off independently from one another andthus have independent power draws. The access points typically are alsolocated remote from one another. One or more electrical appliances ordevices may be associated to a particular access point. Each accesspoint has a specific power draw when it is on (i.e. drawing power fromthe power supply).

In general, queuing access (to the power supply) is controlled in thefollowing manner. The on state and associated power draw of each ofaccess point is identified, and a load duration curve for each accesspoint is normalized (i.e., combined with load duration curve(s)) fromthe other access points) into a probability distribution function. Theprobability distribution function is a normalized load duration curvethat thus accounts for a varying set of “operating states” that mayoccur with respect to the set of access points (when viewedcollectively). Preferably, the probability distribution function is atransformed (or non-normalized) Erlang C probability distributionfunction.

The queuing access method of this disclosure may be implemented in acomputing device associated with one or more electrical power accesspoints that share a power supply. In one embodiment, the probabilitydistribution function is implemented within an electric appliance powerrouter (EAPR), which is a computer system that regulates access to ashared power supply to systematically control coincident peak demand. Inparticular, through associated digital electronic switches (DES) locatedat the access points, the EAPR interprets access point “on” or “off”power draw states as binary data, and queues access to the power supplywith access priority codes (APC) that it supplies to the variousswitches. A particular APC controls turn-on of the access point (inparticular, one or more electrical appliances or devices associatedtherewith). In addition, coincident peak demand is limited to a target“peak-power” threshold while still delivering electric service within agrade of service (GoS) that follows a probability distribution function(e.g., a transformed Erlang distribution)applied to electric power.Preferably, Grade of Service (GoS) is defined with reference to theelectric system peak-power period when its power consumption intensityis the greatest. GoS is the probability of electric power access in apower line group being queued for more than a specified time interval,expressed as a decimal fraction. By queuing access to a shared powersupply in this manner, electrical appliances (associated with the accesspoints) access their power supply in an orderly fashion that minimizesthe power draw collisions that lead to coincident peak demand.

The Erlang Distribution as Applied to Electric Power

The following section provides additional details regarding theprobability distribution function and the use of Erlang C as applied toelectric power. Familiarity with Erlang distributions (and Erlang datatables) is presumed.

The Erlang distribution is a continuous probability distributiondeveloped by A. K. Erlang to examine the number of telephone calls thatmight be made at the same time to switching stations operators. Thiswork on telephone traffic engineering was later expanded to considerwaiting times in queuing systems in general. The Erlang (E) is adimensionless unit used in telephony as a statistical measure of carriedload on service-providing telephone circuits. Offered traffic (inErlangs) is related to the call arrival rate, λ, and the average callholding time, h, by the following relationship: E=λh, provided that hand λ are expressed using the same units of time (seconds and calls persecond, or minutes and calls per minute).

The Erlang B model is a formula for the blocking probability derivedfrom the Erlang distribution to describe the probability of lost callsin a group of circuits. The formula applies under the condition that anunsuccessful call is not queued. The following formula provides theprobability P_(b) that a new call arriving at the circuit group isrejected because all servers (circuits) are busy; in particular, B(E, m)when E Erlang of traffic are offered to m trunks (communicationchannels):

$P_{b} = {{B\left( {E,m} \right)} = \frac{\begin{matrix}E^{m} \\{m\; 1}\end{matrix}}{\sum\limits_{i = 0}^{m}\;\frac{E^{i}}{i\; 1}}}$In the above formula, P_(b) is the probability of blocking, m is thenumber of resources such as servers or circuits in a group, and E=λh isthe total amount of traffic offered in Erlangs.

The Erlang C model expresses the waiting probability in a queuingsystem. If all circuits are busy, the request is queued. An unlimitednumber of requests may be held in the queue simultaneously. Thefollowing formula calculates the probability of queuing carried traffic,assuming that queued calls stay in the system until they can be handled:

$P_{W} = \frac{\frac{A^{N}}{N\; 1}\frac{N}{N - A}}{{\sum\limits_{i = 0}^{N - 1}\;\frac{A^{i}}{i\; 1}} + {\frac{A^{N}}{N\; 1}\frac{N}{N - A}}}$In the above formula, A is the total traffic offered in units ofErlangs, N is the number of servers, and P_(W) is the probability that acustomer has to wait for service.

According to this disclosure, an Erlang distribution is transformed toapply to electric power system planning under a set of assumptions.These assumptions are the following: (i) electric appliances are either“on” or “off” and utilize a group of circuits (electric power wires) toget access to the shared power supply; (ii) electric appliances useelectric power of its group of circuits when they are “on”; (iii)without access control (as provided by the disclosed queuing accessmethod), an electric appliance is serviced by its power supply followingan Erlang B distribution and access is not queued (and the power supplymeets all electric demand all of the time); (iv) a queuing accesscontrol system for electric appliances (according to this disclosure)preferably follows an Erlang C distribution, and queued appliances stayin the system until they can be handled; (v) power supply capacity isequivalent to the “number of servers” in the traditional Erlangdistribution; (vi) average power demand over a period of time isequivalent to “carried load” in the Erlang distribution; and (vii) powersupply capacity equals the power demanded at a given time. Under theseassumptions, the technique transforms the Erlang distribution toelectric power demand according to the following rules. First, the“number of servers” is equivalent to the power supply capacity (P_(S))in Megawatts (MW) times a constant factor “K,” namely: N˜P_(s) (MW)*K.This relationship is represented in the plot in FIG. 1. Second, the“carried traffic” is equivalent to average demand power (P_(D)) inMegawatts (MW) times the same constant factor, namely: E˜P_(D) (MW)*K.

By way of further background, a “load duration curve” (LDC) is used inelectric power generation to illustrate the relationship betweengenerating capacity requirements and capacity utilization. A LDC issimilar to a load curve but the demand data is ordered in descendingorder of magnitude, rather than chronologically. The LDC curve shows thecapacity utilization requirements for each increment of load. The heightof each slice is a measure of capacity, and the width of each slice is ameasure of the utilization rate or capacity factor. The product of thetwo is a measure of electrical energy (e.g. kilowatt hours). FIG. 2illustrates a representative load duration curve for an electric system.A transformed Erlang B distribution applied to electric power models theload duration curve for a given average demand power in Megawatts (MW),where “% time” represents the electric system Grade of Service (GoS).FIG. 3 illustrates a representative load duration curve modeled bytransformed Erlang B. According to this disclosure, a transformed ErlangC distribution applied to electric power models the load duration curvefor a given average demand power in Megawatts (MW), where “% time”represents the system “queuing (% time).” FIG. 4 illustrates arepresentative load duration curve modeled by transformed Erlang C. Whenimplementing a power supply queuing access system according to thisdisclosure, the electric system load duration curve profile changes,increasing its capacity factor while decreasing its coincident peakdemand. FIG. 5 illustrates the electric system load duration curve(s)modeled by transformed Erlang B and C, illustrating the comparison. Forinstance, in an electric system with 2.7 MW average power demand, for apeak demand target threshold at “80% Peak demand” and respective queuingtime at “5% GoS”, coincident peak demand is reduced by 20%.

According to this disclosure, and as described above, the EAPR regulatesaccess to a shared power supply to systematically control coincidentpeak demand. Preferably coincident peak demand is limited to a target“peak-power” threshold while still delivering electric service within aGoS that follows the transformed Erlang C distribution applied toelectric power. FIG. 6 illustrates a representation of EAPR coincidentpeak demand mitigation according to this disclosure.

Implementation

An embodiment of the inventive subject matter is illustrated in FIG. 7.A “system” 700 that operates according to the principles describedherein comprises an electric appliance power router 702, together with aset of digital electronic switches (each, a DES) 704. The nomenclature,such as EAPR or DES, should not be taken as limiting. In general, theEAPR is implemented in automated computing machinery, such as a computersystem. The EAPR may be conceptualized as a “layer” on top of anexisting power line group, and it is the power supply access layer. TheDES may be any SCADA-compliant device or, more generally, anetwork-attached control device. As illustrated, each DES has a dataconnection 705 to the EAPR 702, the data connection may be over any typeof network including, without limitation, fixed line, wireless or somecombination thereof.

In the scenario where wireless communications are used, each of the DESand EAPR may include or have associated therewith a transceiver module.The transceiver module may be configured to communicate using varioustypes of protocols, communication ranges, operating power requirements,RF sub-bands, information types (e.g., voice or data), use scenarios,applications, and the like. Thus, in various embodiments, thetransceiver module may comprise one or more transceivers configured tosupport voice communication for a cellular radiotelephone system such asa GSM, UMTS, CDMA, and/or LTE system. The transceiver module also maycomprise one or more transceivers configured to perform datacommunications in accordance with one or more wireless communicationsprotocols such as WWAN protocols (e.g., GSM/GPRS protocols, CDMA/1xRTTprotocols, EDGE protocols, EV-DO protocols, EV-DV protocols, HSDPAprotocols, Long-Term Evolution protocols, etc.), WLAN protocols (e.g.,IEEE 802.11a/b/g/n, IEEE 802.16, IEEE 802.20, and the like), PANprotocols, infrared protocols, Bluetooth protocols, EMI protocolsincluding passive or active RFID protocols, and the like.

Other protocols and communications methods, e.g., using InternetProtocol (IP)-based networking technologies, SCADA (Supervisory Controland Data Acquisition)-compliant protocols, and the like, may also beused depending on the implementation. The switches 704 compriseelectrical power “access points” with respect to an electric powersystem 706. The power system (or “supply”) 706 is shared among theaccess points. Each access point is distinct in that it has anindependent power draw from the power supply. Thus, each access pointsharing the power supply can turn on/off independently from one another.Typically, the digital electronic switches are positioned in multiplegeographically-dispersed locations, which locations may be remote fromone another, although a pair of switches (each being a distinct accesspoint) may be co-located physically in certain operating environments.As illustrated in FIG. 8, an access point represented by the DES mayhave associated therewith one or more electrical appliances or devices802 and 804. These appliances or devices share the power supply 806.There may be one appliance or device per access point, or more than oneappliance or device.

In general, the EAPR 700 regulates the digital electronic switches (DES)with a queuing order that maximizes the capacity factor of the powersupply 706 (or 806, FIG. 8) and minimizes its coincident peak demandwhile delivering reliable and acceptable electric power service to anyindividual appliance's end-user within a grade of service (GoS). To thisend, the EAPR preferably interprets an access point “on” or “off” powerdraw states as binary data. The EAPR queues access to the shared powersupply (the power system) with so-called “access priority codes” (each,an “APC”) through the digital electronic switches. In particular, theEAPR generates a set of APCs for the access points and provides each DESwith a particular APC. The APC is the relative queuing order assigned toa specific DES. The APC set is generated periodically by the EAPR, andon a continuous basis. For simplicity of explanation only, an accesspoint is assumed to have one electrical appliance associated therewith.An APC is defined using an electric appliance's power draw statisticalmeasure on its electric power line, its end-use service requirements,and, as will be described, an “access priority request” (each, an APR).An APR is a signal given by an end-user that access to the power supplyis needed immediately. This signal may be used to customize an end-usermaximum acceptable queuing time in certain operating environments.

The electric appliance power router (EAPR) performs several functions.It monitors an electric network servers' power draw and limits powerdemand to a target “planned peak-power” threshold for a desired grade ofservice (GoS). To this end, the EAPR communicates access priority codes(APC) to each DES, ensures DES maximum queuing time integrity, andcommutes to minimize individual DES queuing time. The EAPR also performsseveral administrative and management functions, such as authenticatingthe DES devices, collecting and storing DES data, updating DES firmwareor software as needed, and providing a user interface through whichpermitted users can set or program system thresholds, alarms andautomation routines, or obtain reports. Each digital electronic switch(DES) performs several functions. Its main operation is to requestaccess to the power supply, to receive the APC, and to switch electricalpower “on” at its EAPR-designated time on the queue (as determined bythe APC). The DES also provides administrative functions such asauthenticating and establishing secure digital communications with theEAPR, capturing end-user APRs, monitoring an associated appliance'spower draw, and executing EAPR-supplied automation routines andmicro-controller firmware or processor-based software updates.

As noted above, the access priority code (APC) is the relative queuingorder assigned to a specific DES. The APC provided by the EAPR to aparticular DES defines an electric appliance maximum queuing time at agiven moment (or time period). The APC received at a DES is used tominimize total system queuing time when the electric system power draw(e.g., total power draw) is above a target (e.g., “planned peak-power”)threshold and the EAPR starts its access queuing process. The APC takesinto account the respective electric appliance end-use servicerequirements, which typically include one or more of the following:power draw (in watts, which is the average power draw when the electricappliance is “on” during its working cycle); usage time (in minutes,which is the average number of minutes the electric appliance is “on”during its working cycle); usage frequency (in minutes, which is theaverage number of minutes between the “on” times for the electricappliance); location (to identify the approximate geographical locationof the appliance, and to ensure the appliance belongs to a respectiveEAPR electric circuit); end-user maximum acceptable queuing time (inseconds, which is the average time an appliance end-user would accept adelay in the appliance use, and this value may be an industry average,an end-user APR history, or some combination thereof); and an “accesspriority request” (APR) (as noted above, a signal given by the end-userthat access to the power supply is needed immediately). The above set ofone or more parameters are sometimes referred to as “APC parameters.”

FIG. 9 illustrates the basic interaction between a particular DES andthe EAPR. This same interaction is carried out for each DES. At step900, the DES initiates an access request to the EAPR, passingauthentication parameters and the APC parameters (which may include anAPR). At step 902, the EAPR completes the DES authentication andexecutes its queuing routine. The queuing routine is shown in FIG. 10,and it is described below. If the EAPR determines queuing is necessary(i.e., the system is in a “busy” mode), the EAPR sends the APC to theDES. (An APC is also sent to each other DES at this time as well). Thisis step 904. If, on the other hand, the EAPR determines that queuing isnot necessary (i.e., the system is in an “available” mode), the EAPRsends the DES an access request “granted” response. The DES responds atstep 906 by turning “on” the attached appliance either according to theAPC (if in “busy” mode), immediately if either an APR exists or theaccess request “granted” is received (if in “available” mode). At step908, the DES reports actual queuing time and a power draw measure. TheEAPR stores that DES data and updates a DES profile in step 910. Thiscompletes the interaction.

FIG. 10 illustrates the operation of the EAPR queuing prioritizationprocess of this disclosure that is used to grant access to the powersupply that is shared by the access points. According to thisembodiment, and while the electric system total power draw is below aset “planned peak-power” threshold, DES access to power supply isgranted. This is the “available” mode. When the electric network totalpower draw is above the set “peak-power” threshold, however, the EAPRstarts its access queuing process. This is the “busy” mode. Theprioritization process generally works as follows. When electricappliances that are in an “off” state request access to power supply,they are queued. If there is more than “one” DES in the queue, the DESqueuing order is based on their access priority codes. Preferably, APCsalso carry each DES maximum acceptable queuing time (a time whichpreferably should not be exceeded to guarantee service integrity). A DESwith a given APC (e.g., representing a shorter time constraint) willhave a higher priority in the queue over DESs that have higher-valuedAPCs. If desired, APRs may be implemented; as noted above, APRs areend-user requests that give immediate access to power supply, bypassingthe queue.

The process flow begins at step 1000 with a DES making a power supplyaccess request. As noted above, there may be a plurality of DES devices,and each such device may require access to the power supply at any time.A test is performed at step 1002 to determine whether the power supplyis operating below its planned peak-power (or some other designated)threshold. If the outcome of the test at step 1002 is positive, theroutine continues at step 1004 and the DES access request is granted.This is the available mode. If, however, the outcome of the test at step1002 is negative, the peak-power threshold (the GoS) has been met orexceeded. The routine then branches to step 1006 and queuing begins inthe manner previously described. At step 1008, a test is performed todetermine whether an end-user APR is associated with the DES powersupply access request. If so, the routine bypasses the queuing operationand grants the request (by returning to step 1004). If there is no APRassociated with the request, a test is performed at step 1010 todetermine whether the APC for the DES is greater than the maximumavailable queuing time. If so, the routine once again returns to step1004 to grant the access request. If, however, the outcome of the testat step 1010 is negative, a test is performed at step 1012 to determinewhether the DES access request is the next one on the queue. If not, theroutine returns to step 1006 and the queuing process continues. If,however, the outcome of the test step 1012 is positive, then the accessrequest is granted (because the DES's position in the queue has thenbeen reached).

Preferably, if the system state is “busy,” all off state DES are queuedright away. The EAPR also may set a new peak-power threshold when thesystem state changes. In a preferred implementation, this dynamicpeak-power threshold change is carried out each time the system statechanges.

The above-described queuing scheme provides significant advantages. Thetechnique controls coincident peak demand by regulation of the accesspoints (and, in particular, by providing the APCs to the DESs). In thisdemand modulation scheme, the on state and associated power draw of eachof access point is identified, and a load duration curve for each accesspoint is normalized (i.e., combined with load duration curve(s)) fromthe other access points) into a probability distribution function thatis used to drive the queuing process. In effect, the probabilitydistribution function is a normalized load duration curve that thusaccounts for a varying set of “operating states” that may occur withrespect to the set of access points (the set of DESs, when viewedcollectively). Thus, if there are “n” access points (and DESs), thereare 2^(n) possible operating states for the access point set, with eachoperating state being represented by a set of simultaneous “events”corresponding to some subset of the access points (which subset mayinclude all of the access points) being “on” or “off,” as the case maybe. For example, if there are three (3) access points, there are eight(8) possible operating states, corresponding to each of the DES devices(labeled A, B and C) being on (a binary “1”) or off (a binary “0”). Anoperating state such as {0, 0, 1} refers to DES “A” being off, DES Bbeing off, and DES C being on. Each operating state has an associatedprobability of occurrence, and the probabilities add up to 100%. Aparticular operating state may then be set as the “peak-power” threshold(as described above with respect to FIG. 10). The peak-power thresholdtypically represents a grade of service (typically expressed as apercentage or decimal fraction) associated with a particular operatingstate at which queuing is desired (e.g., GoS=2%, representing theoperating state when DES ABC are on, which corresponds to operatingstate { 1, 1, 1}). There may be more than one such threshold thattriggers the queuing operation.

According to the method, as the operating state of the set (of accesspoints) changes (as represented by the on/off events as DES accessrequests are received at the EAPR), access to the power supply isselectively queued, or de-queued (if previously queued). This is theoperation described above with respect to FIG. 10. The one or moreprobability thresholds (the GoS values) define where the system is setto become available (no queuing) or busy (queuing), in effect filteringthe least frequent events (operating states of the access points, viewedcollectively) that demand the highest electric power consumption. Theterms “least frequent” and “highest” as used herein should not be takenas limiting the queuing solution to any particular implementation. Moregenerally, the described approach treats the electric power demand asanalogous to a wave transmission (“on/off” digital wave), and thequeuing operation effectively adjusts the phase of this wave signal,providing a form of phase modulation. Thus, for example, the modulationadjusts the phase of first appliance's operational frequency to minimize“collisions” with one or more other appliance signals, thereforereducing the system aggregate power demand. By reducing demand,electrical power customers receive a significant economic benefit(namely, reduced power costs). In this manner, the queuing techniqueprovides a unique channel access method for an electric power system.

In an alternative embodiment, the technique may be used to increasecoincident demand (i.e. modulating the amplitude of the aggregate wavesignal by making phase adjustments to the individual wave signals).

FIG. 11 illustrates a representative DES. As noted above, preferablythere is a DES associated with an access point, and one or moreelectrical appliances or devices may be associated with a particularDES. Once the EAPR determines that the system is or should be “busy,”the DES uses the APC to enforce the required queuing at the accesspoint. The DES typically is implemented using hardware components, orhardware and software components. As seen in FIG. 11, a representative(but non-limiting implementation) of the DES 1100 comprises severalcomponents: a microcontroller 1102, a switch relay 1104, an electricpower monitor 1106, and a priority switch 1108. As described above, theprimary role of the DES is to request access to power supply and grantit according to EAPR instructions so coincident peak demand ismodulated. In addition, the DES authenticates, reports its power draw tothe EAPR, and performs automation routines. Power draw is monitored bythe power monitor 1106 to detect DES malfunction and profile theappliance's power usage patterns. Power draw, usage frequency, locationand APRs are considered by the EAPR to grant access to the power supply.The DES priority switch 1108 generates end-user access priority requests(APR) in the event a received APC does not reflect immediate end-userservice requirements. The microcontroller 1102 controls the variousfunctions including authenticating and establishing secure digitalcommunications with the EAPR through the data connection, issuing therequests (to the EAPR) to access the power supply, and controllingswitch relay 1104 to switch electric power “on” at a given time based onits queuing order and APC. The microcontroller also captures end-useraccess priority requests generated by the priority switch 1108 andexecutes other EAPR-supplied automation routines. Once it is grantedaccess to the power supply, the DES becomes an active network serverwithin the context of the probability distribution function (e.g., atransformed Erlang C distribution). As such, its power draw is added tothe electric system total power draw and verified against the peak powerthreshold for the queuing algorithm.

One or more sensor-automated appliances (not shown) connect to the DES“sensor's bit” input 1105. Because an appliance sensor is responsiblefor turning the appliance “on,” this bit triggers the EAPR request toaccess power. When access is granted by the EAPR, the “switch bit”output signal 1107 turns the appliance “on,” while the DES power linemonitor circuit 1106 measures the appliance power draw.

FIG. 12 is a plot that represents a statistical measure of an appliancepower draw at a particular DES. As has been described, the APCparameters (power draw, usage time, usage frequency, location, end-usermaximum queuing time, and any APR) are used by the EAPR to define APCsthat prioritize queuing order of electric appliances with shorter usagetime and higher usage frequency relative to other appliances in the EAPRqueue. In addition, a normalized power draw provides a weighting factorthat favors DES with lower power draw in the group of DES at the samelocation according to the following relationships (which are exemplary,but non-limiting):Normalized power draw=Power draw/Max(system's DES power draw)APC=(Normalized power draw)*(usage time)^2/(usage frequency)In one embodiment, the APC value is a DES maximum queuing time, inminutes; preferably, this value does not exceed the minimum of anappliance usage time and its end-user maximum acceptable queuing time:APC≦Minimum (End-user acceptable queuing time, usage time)

By way of example, a system implementing the described solutioncomprises an EAPR and a set of DES (e.g., SCADA-compliant) devices thatcontrol peak demand at locations (which typically are remote) based onthe predictive software algorithm executing in the power router. As hasbeen described, the EAPR operates to minimize access point queuing timeand power draw collisions from the power supply (by predictablycalculating and implementing operational phase shifts), thereby reducingpeak-power demand from the cycling appliances, devices and services thatthe EAPR controls. The DES functionality may be implemented in hardware,firmware or software.

The EAPR (or some functionality thereof) may be implemented within acloud embodiment as a “software-as-a-service.”

The system may be implemented within a single physical facility, acrossmultiple physical facilities, or the like. In an alternative embodiment,the system is implemented in a modular, hierarchical architecture, e.g.,wherein software resident on regional servers provides local monitoringand control of DES devices wirelessly connected thereto, while a centralserver (in which the EAPR executes) oversees the regional servers.

In example embodiments, the DES devices are located withintelecommunications shelters, radio equipment rooms, computer serverrooms, commercial properties, institutional and educational campuses,upstream and downstream oil and gas drilling sites and refineries,electric vehicle charging stations, municipal power systems, governmentfacilities, electric utilities, and others.

The link between the EAPR and a DES preferably is secure. The APC codesmay be transmitted over any IP-based or other transport layer protocolincluding, without limitation, via SMTP as an email message, via NNTP(telnet), via SMS (text) or MMS (multimedia) messages, via HTTP overSOAP (as a web service), or the like. The APCs sent to the DESpreferably are AT (Attention) commands and, as such, can be sent inanalog form. The command sent to the DES is a value that may beunderstood as being “time.” Preferably, the value is updated each timethat the EAPR handshakes with the DES.

The DES functionality may be incorporated into an existingSCADA-compliant or other type of electrical device or appliance. It isnot required that the DES be implemented as a standalone device; rather,the one or more described functions may be added to an existingelectrical device/appliance by a software or other configuration. Inthis approach, a system provider provides the EAPR function (e.g., as acloud-based service) and connects to devices/appliances that have beenconfigured to provide the access point functionality and operationsdescribed. This approach reduces the cost of implementing a turnkeysolution, as it takes advantage of existing hardware at the controlpoint(s).

The demand modulation provided by the disclosed subject matter may beimplemented in any physical arrangement of the EAPR/DES functionalitythat has been described.

The use of Erlang probability distribution as described herein ispreferred but is not intended to limit the disclosed subject matter. TheErlang probability distribution is a special case of a Gammadistribution, and any such distribution may be used as well. Otherprobability distributions that may be applied include the Poissondistribution, the Pareto distribution, the Bernoulli processdistribution, and the Engset calculation.

The system components as have been described are a representativeembodiment. It is not required that all such components be included, orthat the identified boundaries be as shown. One of more components maybe combined or associated with the system or other entities, as the casemay be, without departing from the scope of the described subjectmatter. It is not required that the components be located within thesame data center. The EAPR or DES comprises computing machinery andassociated electronics and/or mechanical devices as needed. Thefunctions described may be implemented by machines, devices, programs,controllers, switches, processes, execution threads, and the like.

While the above describes a particular order of operations performed bycertain embodiments of the invention, it should be understood that suchorder is exemplary, as alternative embodiments may perform theoperations in a different order, combine certain operations, overlapcertain operations, or the like. References in the specification to agiven embodiment indicate that the embodiment described may include aparticular feature, structure, or characteristic, but every embodimentmay not necessarily include the particular feature, structure, orcharacteristic.

The subject matter herein can take the form of an entirely hardwareembodiment, an entirely software embodiment, or an embodiment containingboth hardware and software elements. In one embodiment, thefunctionality is implemented in software executing in one or more servermachines. The disclosed system (or portions thereof) may take the formof a computer program product accessible from a computer-usable orcomputer-readable medium providing program code for use by or inconnection with a computer or any instruction execution system. Acomputer-usable or computer readable medium can be any device orapparatus that can store the program for use by or in connection withthe instruction execution system, apparatus, or device. The medium canbe an electronic, magnetic, optical, or the like. Examples of acomputer-readable medium include a semiconductor or solid state memory,magnetic tape, a removable computer diskette, a random access memory(RAM), a read-only memory (ROM), a rigid magnetic disk and an opticaldisk. Current examples of optical disks include compact disk—read onlymemory (CD-ROM), compact disk—read/write (CD-R/W) and DVD.

While given components of the system have been described separately, oneof ordinary skill will appreciate that some of the functions may becombined or shared in given instructions, program sequences, codeportions, and the like.

Having described our invention, what we now claim is as follows: 1.Apparatus to queue access to a power supply shared by a set ofelectrical entities, wherein each electrical entity has a power drawvalue associated with the electrical entity being in an on state, thepower draw value associated with a load duration curve, comprising: ahardware processor; computer memory holding computer programinstructions, the computer program instructions executed by the hardwareprocessor to: normalize the load duration curves for a set of operatingstates of the electrical entities to generate a probability distributionfunction, the probability distribution function having a set ofprobability thresholds corresponding to the number of operating states,the probability thresholds including at least one threshold representinga particular grade of service (GoS) at which access to the power supplyshould be queued; queue access to the power supply when, in response toa first change in operating state, the threshold representing the gradeof service is met, wherein queuing access to the power supply adjusts aturn-on of an electrical entity; and de-queue access to the power supplywhen, in response to a second change in operating state, the thresholdrepresenting the grade of service ceases to be met.
 2. The apparatus asdescribed in claim 1 wherein the turn-on is adjusted by the computerprogram instructions providing an access priority code, the accesspriority code being a member of a set of access priority codes (APCs)that define a relative queuing order operative to minimize individualpower draw collisions from the power supply.
 3. The apparatus asdescribed in claim 2 wherein an access priority code (APC) is a functionof an end-use service requirement associated with the electrical entity.4. The apparatus as described in claim 1 wherein the probabilitydistribution function is one of: a Gamma distribution, a Poissondistribution, a Pareto distribution, a Bernoulli process distribution,and an Engset calculation.
 5. The apparatus as described in claim 4wherein the Gamma distribution is a transformed Erlang C probabilitydistribution function models a load duration curve associating a totalpower demand for the particular grade of service.
 6. The apparatus asdescribed in claim 1 wherein the program instructions are operative tore-generate the probability distribution function continuously.
 7. Theapparatus as described in claim 1 wherein the electrical entities areassociated with a commercial property.
 8. The apparatus as described inclaim 1 wherein the electrical entities are load drawing appliances. 9.The apparatus as described in claim 1 wherein the electrical entitiesare load storing devices.